code: def test_kernel_symkl(self):
      kernel = GaussianSymmetrizedKLKernel()
      kernel.lengthscale = 1.0
  
      values = torch.rand(100, 20)
      base_value = torch.zeros(1, 20)
      kernel_output = kernel(values, base_value)
      self.assertEqual(kernel_output.shape, torch.Size((100, 1)))
  
      value_means = values[..., :10]
      value_stds = (1e-8 + values[..., 10:].exp()) ** 0.5
      value_dist = Normal(
          value_means.unsqueeze(0), value_stds.unsqueeze(0)
      )
  
      base_dist = Normal(torch.zeros(1, 10), torch.ones(1, 10))
  
      result = -(
          kl_divergence(value_dist, base_dist)
          + kl_divergence(base_dist, value_dist)
      ).sum(-1)
      self.assertLessEqual(
          (
              kernel_output.to_dense() - result.exp().transpose(-2, -1)
          ).norm(),
          1e-5,
      )
  
file_path: gpytorch/test/kernels/test_gaussian_symmetrized_kl_kernel.py
imports: import unittest
  import torch
  from torch.distributions import kl_divergence, Normal
  from gpytorch.kernels import GaussianSymmetrizedKLKernel
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 1 for calling the TestGaussianSymmetrizedKLKernel obj's underlying member method code with example usage: obj.test_kernel_symkl() without return types